Triple

T11712689
Position Surface form Disambiguated ID Type / Status
Subject Artaserse E278410 entity
Predicate featuresCharacter P626 FINISHED
Object Megabise
Megabise is a character in the 18th-century opera "Artaserse," typically portrayed as a powerful and scheming Persian noble involved in the court’s political intrigues.
 E942046 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Megabise | Statement: [Artaserse, featuresCharacter, Megabise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Megabise
Context triple: [Artaserse, featuresCharacter, Megabise]
  • A. Megeb
    Megeb is a dialect of the Dargin language spoken by the Dargin people of the North Caucasus region in Dagestan, Russia.
  • B. Muchik
    Muchik is an extinct indigenous language once spoken by the Mochica people along Peru’s northern coast.
  • C. Banzebi
    Banzebi are a subgroup of the Nzebi people, an ethnic community primarily found in Central Africa, especially in Gabon and surrounding regions.
  • D. Mambae
    Mambae is an Austronesian language spoken primarily in the central and eastern regions of Timor-Leste.
  • E. Bimoba
    Bimoba are an ethnic group primarily inhabiting parts of northern Ghana and neighboring areas of Togo, known for their distinct language and cultural traditions.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Megabise
Triple: [Artaserse, featuresCharacter, Megabise]
Generated description
Megabise is a character in the 18th-century opera "Artaserse," typically portrayed as a powerful and scheming Persian noble involved in the court’s political intrigues.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Megabise
Target entity description: Megabise is a character in the 18th-century opera "Artaserse," typically portrayed as a powerful and scheming Persian noble involved in the court’s political intrigues.
  • A. Megeb
    Megeb is a dialect of the Dargin language spoken by the Dargin people of the North Caucasus region in Dagestan, Russia.
  • B. Muchik
    Muchik is an extinct indigenous language once spoken by the Mochica people along Peru’s northern coast.
  • C. Banzebi
    Banzebi are a subgroup of the Nzebi people, an ethnic community primarily found in Central Africa, especially in Gabon and surrounding regions.
  • D. Mambae
    Mambae is an Austronesian language spoken primarily in the central and eastern regions of Timor-Leste.
  • E. Bimoba
    Bimoba are an ethnic group primarily inhabiting parts of northern Ghana and neighboring areas of Togo, known for their distinct language and cultural traditions.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4be10088190854699385d1f6a95 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef838562d08190b9a764e88c50d423 completed April 27, 2026, 3:40 p.m.
NEDg Description generation batch_69ef9b68309081909f3f614efeeb2ab1 completed April 27, 2026, 5:22 p.m.
NED2 Entity disambiguation (via description) batch_69efd6aba82c81909ff22e6b26db3cfe completed April 27, 2026, 9:35 p.m.
Created at: April 8, 2026, 9:40 p.m.